"""
AI Validators - Consolidated validation logic for all AI functions
"""
import logging
from typing import Dict, Any, Optional
from django.utils import timezone

logger = logging.getLogger(__name__)


def validate_ids(payload: dict, max_items: Optional[int] = None) -> Dict[str, Any]:
    """
    Base validation: checks for 'ids' array.
    
    Args:
        payload: Request payload containing 'ids' array
        max_items: Maximum number of items allowed (deprecated - no longer enforced)
    
    Returns:
        Dict with 'valid' (bool) and optional 'error' (str)
    """
    ids = payload.get('ids', [])
    if not ids:
        return {'valid': False, 'error': 'No IDs provided'}
    
    # Removed max_items limit check - no limits enforced
    
    return {'valid': True}


def validate_keywords_exist(ids: list, account=None) -> Dict[str, Any]:
    """
    Validate that keywords exist in database.
    
    Args:
        ids: List of keyword IDs
        account: Optional account for filtering
    
    Returns:
        Dict with 'valid' (bool) and optional 'error' (str)
    """
    from igny8_core.modules.planner.models import Keywords
    
    queryset = Keywords.objects.filter(id__in=ids)
    if account:
        queryset = queryset.filter(account=account)
    
    if queryset.count() == 0:
        return {'valid': False, 'error': 'No keywords found'}
    
    return {'valid': True}


def validate_cluster_limits(account, operation_type: str = 'cluster') -> Dict[str, Any]:
    """
    Validate plan limits for cluster operations.
    DISABLED: All limits have been removed.
    
    Args:
        account: Account object
        operation_type: Type of operation ('cluster', 'idea', etc.)
    
    Returns:
        Dict with 'valid' (bool) - always returns valid
    """
    # All limits removed - always return valid
    return {'valid': True}


def validate_cluster_exists(cluster_id: int, account=None) -> Dict[str, Any]:
    """
    Validate that a cluster exists.
    
    Args:
        cluster_id: Cluster ID
        account: Optional account for filtering
    
    Returns:
        Dict with 'valid' (bool) and optional 'error' (str)
    """
    from igny8_core.modules.planner.models import Clusters
    
    queryset = Clusters.objects.filter(id=cluster_id)
    if account:
        queryset = queryset.filter(account=account)
    
    if not queryset.exists():
        return {'valid': False, 'error': 'Cluster not found'}
    
    return {'valid': True}


def validate_tasks_exist(task_ids: list, account=None) -> Dict[str, Any]:
    """
    Validate that tasks exist in database.
    
    Args:
        task_ids: List of task IDs
        account: Optional account for filtering
    
    Returns:
        Dict with 'valid' (bool) and optional 'error' (str)
    """
    from igny8_core.modules.writer.models import Tasks
    
    queryset = Tasks.objects.filter(id__in=task_ids)
    if account:
        queryset = queryset.filter(account=account)
    
    if queryset.count() == 0:
        return {'valid': False, 'error': 'No tasks found'}
    
    return {'valid': True}


def validate_api_key(api_key: Optional[str], integration_type: str = 'openai') -> Dict[str, Any]:
    """
    Validate that API key is configured.
    
    Args:
        api_key: API key to validate
        integration_type: Type of integration ('openai', 'runware')
    
    Returns:
        Dict with 'valid' (bool) and optional 'error' (str)
    """
    if not api_key:
        return {
            'valid': False,
            'error': f'{integration_type.upper()} API key not configured'
        }
    
    return {'valid': True}


def validate_model(model: str, model_type: str = 'text') -> Dict[str, Any]:
    """
    Validate that model is in supported list using database.
    
    Args:
        model: Model name to validate
        model_type: Type of model ('text' or 'image')
    
    Returns:
        Dict with 'valid' (bool) and optional 'error' (str)
    """
    try:
        # Try database first
        from igny8_core.business.billing.models import AIModelConfig
        
        exists = AIModelConfig.objects.filter(
            model_name=model,
            model_type=model_type,
            is_active=True
        ).exists()
        
        if not exists:
            # Get available models for better error message
            available = list(AIModelConfig.objects.filter(
                model_type=model_type,
                is_active=True
            ).values_list('model_name', flat=True))
            
            if available:
                return {
                    'valid': False,
                    'error': f'Model "{model}" is not active or not found. Available {model_type} models: {", ".join(available)}'
                }
            else:
                return {
                    'valid': False,
                    'error': f'Model "{model}" is not found in database'
                }
        
        return {'valid': True}
        
    except Exception:
        # Fallback to constants if database fails
        from .constants import MODEL_RATES, VALID_OPENAI_IMAGE_MODELS
        
        if model_type == 'text':
            if model not in MODEL_RATES:
                return {
                    'valid': False,
                    'error': f'Model "{model}" is not in supported models list'
                }
        elif model_type == 'image':
            if model not in VALID_OPENAI_IMAGE_MODELS:
                return {
                    'valid': False,
                    'error': f'Model "{model}" is not valid for OpenAI image generation. Only {", ".join(VALID_OPENAI_IMAGE_MODELS)} are supported.'
                }
        
        return {'valid': True}


def validate_image_size(size: str, model: str) -> Dict[str, Any]:
    """
    Validate that image size is valid for the selected model using database.
    
    Args:
        size: Image size (e.g., '1024x1024')
        model: Model name
    
    Returns:
        Dict with 'valid' (bool) and optional 'error' (str)
    """
    try:
        # Try database first
        from igny8_core.business.billing.models import AIModelConfig
        
        model_config = AIModelConfig.objects.filter(
            model_name=model,
            model_type='image',
            is_active=True
        ).first()
        
        if model_config:
            if not model_config.validate_size(size):
                valid_sizes = model_config.valid_sizes or []
                return {
                    'valid': False,
                    'error': f'Image size "{size}" is not valid for model "{model}". Valid sizes are: {", ".join(valid_sizes)}'
                }
            return {'valid': True}
        else:
            return {
                'valid': False,
                'error': f'Image model "{model}" not found in database'
            }
            
    except Exception:
        # Fallback to constants if database fails
        from .constants import VALID_SIZES_BY_MODEL
        
        valid_sizes = VALID_SIZES_BY_MODEL.get(model, [])
        if size not in valid_sizes:
            return {
                'valid': False,
                'error': f'Image size "{size}" is not valid for model "{model}". Valid sizes are: {", ".join(valid_sizes)}'
            }
        
        return {'valid': True}